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Publication
154views
13 years 19 hour ago
Preference elicitation and inverse reinforcement learning
We state the problem of inverse reinforcement learning in terms of preference elicitation, resulting in a principled (Bayesian) statistical formulation. This generalises previous w...
Constantin Rothkopf, Christos Dimitrakakis
ICML
2010
IEEE
13 years 10 months ago
Inverse Optimal Control with Linearly-Solvable MDPs
We present new algorithms for inverse optimal control (or inverse reinforcement learning, IRL) within the framework of linearlysolvable MDPs (LMDPs). Unlike most prior IRL algorit...
Dvijotham Krishnamurthy, Emanuel Todorov
IDA
2009
Springer
14 years 4 months ago
Image Denoising Using Sparse Representations
The problem of removing white zero-mean Gaussian noise from an image is an interesting inverse problem to be investigated in this paper through sparse and redundant representations...
Seyyed Majid Valiollahzadeh, Hamed Firouzi, Massou...
CDC
2009
IEEE
166views Control Systems» more  CDC 2009»
14 years 1 months ago
Stable inversion-based robust tracking control in DC-DC nonlinear switched converters
— This article studies the robust tracking control problem in nonminimum phase DC-DC nonlinear switched power converters. The proposed procedure introduces a stable inversion-bas...
Josep M. Olm, Xavier Ros, Yuri B. Shtessel

Publication
240views
12 years 8 months ago
Bayesian multitask inverse reinforcement learning
We generalise the problem of inverse reinforcement learning to multiple tasks, from multiple demonstrations. Each one may represent one expert trying to solve a different task, or ...
Christos Dimitrakakis, Constantin A. Rothkopf